Decoupling control method and device for air system of fuel cell engine

Abstract

The invention relates to the technical field of fuel cells, in particular to a decoupling control method and device for a fuel cell engine air system, and the method comprises the steps: obtaining the pressure ratio of an air compressor through the outlet pressure and inlet pressure of the air compressor of the air system; the surge boundary mass flow of the air system is determined according to the pressure ratio of the air compressor, so that the air system is subjected to surge correction treatment according to the actual flow of the outlet of the air compressor; and the cathode stoichiometric ratio error and the cathode inlet pressure error determined based on the surge correction result of the air system are input into a fuzzy PID controller based on the improved particle swarm algorithm, the rotating speed of an air compressor and the opening degree of a back pressure valve are obtained, and decoupling control is conducted on the air system. According to the embodiment of the invention, surge correction treatment can be carried out on the air system, and the cathode stoichiometric ratio error and the cathode inlet pressure error are input into the fuzzy PID controller based on the improved particle swarm algorithm, so that decoupling control is carried out on the air system, and the operation stability of the air system is effectively improved.

Description

Technical Field

[0001] The present application relates to the field of fuel cell technology, and in particular to a decoupling control method and device for a fuel cell engine air system. Background Art

[0002] The air subsystem of a fuel cell engine is a nonlinear, strongly coupled, time-varying system. The control of the air system should have certain robustness and anti-interference capabilities, which makes the control of the air system more difficult. On the other hand, the parameters of the air system (air flow, pressure, temperature and humidity) will directly affect the output characteristics of the fuel cell system. During the operation of the system, it is necessary to ensure that the state of the air entering the stack meets its performance index requirements, otherwise it will directly affect the system efficiency, fuel cell performance and life.

[0003] In the related art, the difference between the pressure and the feedback pressure is output as the back pressure valve opening through an improved PR algorithm, and the difference between the flow and the feedback flow is output as the air compressor speed through an improved PR algorithm. That is, the flow and pressure are decoupled by using an improved PR controller, and the outputs of the PR controller are the air compressor speed and the back pressure valve opening, respectively, to achieve decoupling of the air subsystem of the fuel cell engine.

[0004] However, the improved PR controller used in the related art to decouple flow and pressure is not suitable for performance under low-frequency disturbances, resulting in air compressor surge in the low-power range, reducing the stability of the air subsystem operation, and reducing the response speed and operating efficiency of the air subsystem, which urgently needs to be solved. Summary of the invention

[0005] The present application provides a decoupling control method and device for a fuel cell engine air system to solve the problem that the decoupling of flow and pressure by using an improved PR controller in the related art cannot be applied to the performance under low-frequency disturbances, resulting in air compressor surge in the low-power range, reducing the stability of the air subsystem operation, and reducing the response speed and operating efficiency of the air subsystem.

[0006] The first aspect of the present application provides a decoupling control method for a fuel cell engine air system, comprising the following steps: obtaining the actual air compressor outlet flow, air compressor inlet pressure and air compressor outlet pressure of the air system of the fuel cell engine, and obtaining the air compressor pressure ratio of the air system using the air compressor outlet pressure and the air compressor inlet pressure; determining the surge boundary mass flow of the air system according to the air compressor pressure ratio, and performing surge correction processing on the air system using the surge boundary mass flow and the actual air compressor outlet flow to obtain a surge correction result of the air system; determining the cathode stoichiometric ratio error and the cathode inlet pressure error of the fuel cell stack based on the surge correction result, and inputting the cathode stoichiometric ratio error and the cathode inlet pressure error into a fuzzy PID (Proportional-Integral-Derivative Controller) controller based on an improved particle swarm algorithm, respectively, to obtain the air compressor speed and back pressure valve opening of the air system, so as to perform decoupling control on the air system of the fuel cell engine.

[0007] Through the above-mentioned technical means, the embodiment of the present application can perform surge correction processing on the air system, and input the cathode stoichiometric ratio error and cathode inlet pressure error of the fuel cell stack determined by the surge correction results of the air system into the fuzzy PID controller based on the improved particle swarm algorithm, so as to decouple the air system of the fuel cell engine and effectively improve the stability of the air system operation.

[0008] Optionally, in one embodiment of the present application, determining the surge boundary mass flow rate of the air system according to the air compressor pressure ratio includes: establishing a surge boundary equation using multiple target test data; and determining the surge boundary mass flow rate of the air system based on the surge boundary equation and the air compressor pressure ratio.

[0009] Through the above technical means, the embodiment of the present application can use the surge boundary equation and the air compressor pressure ratio to determine the surge boundary mass flow of the air system, thereby improving the accuracy of the air compressor surge correction of the air system.

[0010] Optionally, in one embodiment of the present application, the surge correction processing of the air system using the surge boundary mass flow and the actual flow at the air compressor outlet includes: detecting whether the surge boundary mass flow is greater than or equal to the actual flow at the air compressor outlet; when it is detected that the surge boundary mass flow is greater than or equal to the actual flow at the air compressor outlet, obtaining the bypass valve opening of the air system; and performing surge correction processing on the air system using the bypass valve opening.

[0011] Through the above technical means, the embodiment of the present application can control the bypass valve of the air system through the opening of the bypass valve of the air system, so as to bypass part of the air flow to increase the total air flow, thereby avoiding the occurrence of surge.

[0012] Optionally, in one embodiment of the present application, obtaining the bypass valve opening of the air system includes: obtaining an error value between the surge boundary mass flow and the actual flow at the air compressor outlet; determining a control input of the bypass valve of the air system according to the error value; and determining the bypass valve opening of the air system using the control input.

[0013] Through the above-mentioned technical means, the embodiment of the present application can determine the bypass valve opening of the air system, effectively avoid the air compressor surge phenomenon in the air system, thereby improving the stability and efficiency of the system.

[0014] Optionally, in one embodiment of the present application, determining the cathode metering ratio error and the cathode inlet pressure error of the fuel cell stack includes: obtaining the actual metering ratio of the cathode inlet of the fuel cell stack, and determining the cathode metering ratio error based on the cathode target metering ratio of the fuel cell stack and the actual cathode metering ratio; determining the cathode inlet pressure error based on the cathode inlet target pressure of the fuel cell stack and the actual cathode inlet pressure.

[0015] Through the above-mentioned technical means, the embodiments of the present application can respectively determine the cathode stoichiometric ratio error and the cathode inlet pressure error of the fuel cell stack to ensure the stable operation of the fuel cell.

[0016] The second aspect of the present application provides a decoupling control device for a fuel cell engine air system, comprising: an acquisition module, used to acquire the actual air compressor outlet flow, air compressor inlet pressure and air compressor outlet pressure of the air system of the fuel cell engine, and use the air compressor outlet pressure and the air compressor inlet pressure to obtain the air compressor pressure ratio of the air system; a determination module, used to determine the surge boundary mass flow of the air system according to the air compressor pressure ratio, and use the surge boundary mass flow and the actual air compressor outlet flow to perform surge correction processing on the air system to obtain a surge correction result of the air system; a control module, used to determine the cathode stoichiometric ratio error and the cathode inlet pressure error of the fuel cell stack based on the surge correction result, and input the cathode stoichiometric ratio error and the cathode inlet pressure error into a fuzzy PID controller based on an improved particle swarm algorithm, respectively, to obtain the air compressor speed and back pressure valve opening of the air system, so as to perform decoupling control on the air system of the fuel cell engine.

[0017] Through the above-mentioned technical means, the decoupling control device of the fuel cell engine air system can perform surge correction processing on the air system, and input the cathode stoichiometric ratio error and cathode inlet pressure error of the fuel cell stack determined by the surge correction result of the air system into the fuzzy PID controller based on the improved particle swarm algorithm, so as to perform decoupling control on the air system of the fuel cell engine, thereby effectively improving the stability of the air system operation.

[0018] Optionally, in one embodiment of the present application, the determination module includes: an establishment unit for establishing a surge boundary equation using multiple target test data; and a first determination unit for determining the surge boundary mass flow rate of the air system based on the surge boundary equation and the air compressor pressure ratio.

[0019] Through the above technical means, the determination module can use the surge boundary equation and the air compressor pressure ratio to determine the surge boundary mass flow of the air system, thereby improving the accuracy of the air compressor surge correction of the air system.

[0020] Optionally, in one embodiment of the present application, the determination module includes: a detection unit, used to detect whether the surge boundary mass flow rate is greater than or equal to the actual flow rate at the air compressor outlet; a first acquisition unit, used to obtain the bypass valve opening of the air system when it is detected that the surge boundary mass flow rate is greater than or equal to the actual flow rate at the air compressor outlet; and a processing unit, used to perform surge correction processing on the air system using the bypass valve opening.

[0021] Through the above technical means, the determination module can control the bypass valve of the air system through the bypass valve opening of the air system, so as to bypass part of the air flow to increase the total air flow, thereby avoiding the occurrence of surge.

[0022] Optionally, in one embodiment of the present application, the first acquisition unit includes: an acquisition subunit, used to obtain the error value between the surge boundary mass flow and the actual flow at the air compressor outlet; a first determination subunit, used to determine the control input of the bypass valve of the air system according to the error value; and a second determination subunit, used to determine the opening of the bypass valve of the air system using the control input.

[0023] Through the above-mentioned technical means, the embodiment of the present application can determine the bypass valve opening of the air system, effectively avoid the air compressor surge phenomenon in the air system, thereby improving the stability and efficiency of the system.

[0024] Optionally, in one embodiment of the present application, the control module includes: a second acquisition unit, used to acquire the actual cathode inlet metering ratio of the fuel cell stack, and determine the cathode metering ratio error based on the cathode target metering ratio of the fuel cell stack and the cathode actual metering ratio; a second determination unit, used to determine the cathode inlet pressure error based on the cathode inlet target pressure of the fuel cell stack and the cathode inlet actual pressure.

[0025] Through the above technical means, the control module can respectively determine the cathode stoichiometric ratio error and the cathode inlet pressure error of the fuel cell stack to ensure the stable operation of the fuel cell.

[0026] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the decoupling control method of the fuel cell engine air system as described in the above embodiment.

[0027] A fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the above-mentioned decoupling control method for the fuel cell engine air system.

[0028] A fifth aspect of the present application provides a computer program product, including a computer program, which, when executed, is used to implement the above-mentioned decoupling control method for the fuel cell engine air system.

[0029] The embodiment of the present application can perform surge correction processing on the air system, and input the cathode metering ratio error and cathode inlet pressure error of the fuel cell stack determined by the surge correction result of the air system into the fuzzy PID controller based on the improved particle swarm algorithm, so as to decouple the air system of the fuel cell engine and effectively improve the stability of the air system operation. Thus, the problem that the decoupling of flow and pressure using the improved PR controller in the related art cannot be applied to the performance under low-frequency disturbance, resulting in the occurrence of air compressor surge in the low-power range, reducing the stability of the air subsystem operation, and reducing the response speed and operating efficiency of the air subsystem.

[0030] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0032] Figure 1 A schematic diagram of an air system of a fuel cell engine provided according to an embodiment of the present application;

[0033] Figure 2 A flowchart of a decoupling control method for a fuel cell engine air system provided according to an embodiment of the present application;

[0034] Figure 3 This is a schematic diagram of optimizing fuzzy PID control parameters using an improved particle swarm optimization algorithm according to a specific embodiment of the present application;

[0035] Figure 4 This is a comparison chart of the control effects of the stoichiometric ratio of the fuzzy PID controller optimized by the improved particle swarm optimization algorithm and the PID controller in a specific embodiment of the present application;

[0036] Figure 5 This is a comparison diagram of the back pressure control effects of the fuzzy PID controller optimized by the improved particle swarm optimization algorithm and the PID controller in a specific embodiment of the present application;

[0037] Figure 6 This is a flowchart of an improved particle swarm optimization algorithm for a specific embodiment of the present application;

[0038] Figure 7 It is a structural schematic diagram of a decoupling control device for a fuel cell engine air system provided according to an embodiment of the present application;

[0039] Figure 8 It is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0040] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0041] The following describes the decoupling control method and device of the fuel cell engine air system of the embodiment of the present application with reference to the accompanying drawings. In view of the above-mentioned related technology mentioned in the background technology center, the improved PR controller is used to decouple the flow and pressure, which cannot be applied to the performance under low-frequency disturbance, resulting in the occurrence of air compressor surge in the low power range, reducing the stability of the air subsystem operation, and reducing the response speed and operation efficiency of the air subsystem. The present application provides a decoupling control method for the air system of a fuel cell engine, in which the air system can be subjected to surge correction processing, and the cathode stoichiometric ratio error and cathode inlet pressure error of the fuel cell stack determined by the surge correction result of the air system are respectively input into the fuzzy PID controller based on the improved particle swarm algorithm to decouple the air system of the fuel cell engine, effectively improving the stability of the air system operation. Thus, the problem that the improved PR controller is used to decouple the flow and pressure in the related technology, which cannot be applied to the performance under low-frequency disturbance, resulting in the occurrence of air compressor surge in the low power range, reducing the stability of the air subsystem operation, and reducing the response speed and operation efficiency of the air subsystem is solved.

[0042] like Figure 1 As shown, the embodiment of the present application establishes a fuel cell air path model, including an air filter, an air compressor, an intercooler, a humidifier, a bypass valve, and a back pressure valve.

[0043] Among them, the air path model, that is, the air system provides the fuel cell stack with air of suitable pressure, flow, temperature and humidity to participate in the reaction; the air compressor is used to provide the air required for the fuel cell stack reaction process; the intercooler is used to cool the compressed air; the humidifier is used to humidify the dry air after passing through the intercooler to meet the inlet humidity requirement of the fuel cell engine; the bypass valve is mainly used to discharge excess gas flow at low power to prevent air compressor surge; the back pressure valve mainly controls the fuel cell engine outlet pressure by adjusting the valve opening to establish the working demand pressure of the fuel cell engine.

[0044] Specifically, Figure 2 A schematic flow chart of a decoupling control method for a fuel cell engine air system provided in an embodiment of the present application.

[0045] like Figure 2 As shown, the decoupling control method of the fuel cell engine air system includes the following steps:

[0046] In step S201, the actual air compressor outlet flow, air compressor inlet pressure and air compressor outlet pressure of the air system of the fuel cell engine are obtained, and the air compressor pressure ratio of the air system is obtained using the air compressor outlet pressure and air compressor inlet pressure.

[0047] It can be understood that the embodiment of the present application can obtain the actual air compressor outlet flow, air compressor inlet pressure and air compressor outlet pressure of the air system of the fuel cell engine, and use the air compressor outlet pressure and air compressor inlet pressure to obtain the air compressor pressure ratio of the air system. For example, the embodiment of the present application can process the various sensor signals in the fuel cell engine to obtain the actual cathode inlet pressure P of the stack. act , Actual flow rate of air compressor outlet of air system m act , air compressor inlet pressure P in and air compressor outlet pressure P out , and the air compressor outlet pressure P out Divide by the compressor inlet pressure P in Get the air compressor pressure ratio P r , effectively improving the feasibility of air system decoupling.

[0048] In step S202, the surge boundary mass flow of the air system is determined according to the air compressor pressure ratio, and the surge boundary mass flow and the actual flow at the air compressor outlet are used to perform surge correction processing on the air system to obtain a surge correction result of the air system.

[0049] It can be understood that the embodiment of the present application can determine the surge boundary mass flow rate of the air system according to the air compressor pressure ratio in the following steps, and use the surge boundary mass flow rate in the following steps and the actual flow rate at the air compressor outlet to perform surge correction processing on the air system, that is, to determine whether air compressor surge correction is needed to obtain a surge correction result for the air system, which can effectively avoid the air compressor from sending surge and effectively improve the accuracy of the air system.

[0050] Among them, in one embodiment of the present application, the surge boundary mass flow rate of the air system is determined according to the air compressor pressure ratio, including: using multiple target test data to establish a surge boundary equation; based on the surge boundary equation and the air compressor pressure ratio, determining the surge boundary mass flow rate of the air system.

[0051] In some embodiments, the embodiments of the present application can use the air compressor surge boundaries obtained from multiple tests. For example, different pressure ratios and corresponding minimum stable surge boundary mass flow rates are obtained through tests under different operating conditions, and an equation of surge boundary flow rate and pressure ratio is established, that is:

[0052] m am =f(P r )

[0053] Among them, m am represents the surge boundary mass flow rate, f(P r ) represents the equation relating flow rate to pressure ratio.

[0054] Therefore, the embodiment of the present application can determine the surge boundary mass flow rate of the air system based on the surge boundary equation and the above-collected air compressor pressure ratio, thereby improving the accuracy of the air compressor surge correction of the air system.

[0055] Among them, in one embodiment of the present application, the air system is subjected to surge correction processing using the surge boundary mass flow and the actual flow at the air compressor outlet, including: detecting whether the surge boundary mass flow is greater than or equal to the actual flow at the air compressor outlet; when it is detected that the surge boundary mass flow is greater than or equal to the actual flow at the air compressor outlet, obtaining the bypass valve opening of the air system; and performing surge correction processing on the air system using the bypass valve opening.

[0056] For example, in the embodiment of the present application, the surge boundary mass flow rate m am And the actual flow rate of the air compressor outlet m act Compare the sizes to determine whether the air compressor in the air system needs surge correction. am Less than m act When m am Greater than or equal to m act When , it indicates that there is a surge risk and the bypass valve needs to be opened, so that the bypass valve opening of the air system in the following steps can be obtained, and the total air flow can be increased by bypassing part of the air flow, thereby avoiding the occurrence of surge.

[0057] Optionally, in one embodiment of the present application, obtaining the bypass valve opening of the air system includes: obtaining the error value between the surge boundary mass flow and the actual flow at the air compressor outlet; determining the control input of the bypass valve of the air system according to the error value; and determining the bypass valve opening of the air system using the control input.

[0058] For another example, in the embodiment of the present application, the surge boundary mass flow rate m am The actual flow rate at the air compressor outlet m act Subtract the error value e of mass flow m , the error value e m Input into the PI regulator to obtain the bypass valve control input i m Then, the bypass valve control input i m Input into the bypass valve controller to obtain the bypass valve opening k v , thereby bypassing excess gas and effectively avoiding air compressor surge in the air system, thereby improving system stability and efficiency.

[0059] In step S203, based on the surge correction result, the cathode stoichiometric ratio error and cathode inlet pressure error of the fuel cell stack are determined, and the cathode stoichiometric ratio error and cathode inlet pressure error are respectively input into the fuzzy PID controller based on the improved particle swarm algorithm to obtain the air compressor speed and back pressure valve opening of the air system, so as to decouple the air system of the fuel cell engine.

[0060] It can be understood that the embodiments of the present application can determine the cathode stoichiometric ratio error and cathode inlet pressure error of the fuel cell stack in the following steps based on the surge correction result, and input the cathode stoichiometric ratio error and cathode inlet pressure error into the fuzzy PID controller based on the improved particle swarm algorithm, respectively, to optimize the control parameters of the fuzzy PID, thereby obtaining the air compressor speed and back pressure valve opening of the air system, so as to decouple the air system of the fuel cell engine, greatly improve the control accuracy and response speed, reduce the overshoot, and effectively improve the stability of the air system operation.

[0061] For example, Figure 3 As shown, the embodiment of the present application can be used to calculate the air metering ratio difference e λ The pressure difference with the cathode inlet P Input it into the corresponding fuzzy PID controller to get the air compressor speed S AC and back pressure valve opening O bpv Then, the embodiment of the present application can use an improved particle swarm algorithm to optimize the PID controller, take the integral minimum of the absolute value of the difference between the actual metering ratio and the theoretical calculated metering ratio as the optimization target, and use the improved particle swarm algorithm optimization control method to optimize this value of the fuzzy PID controller, where de / dt represents the rate of change of error.

[0062] The basic particle swarm algorithm solves the optimal fitness value of particles by updating the moving speed of candidate solutions. The formula is as follows:

[0063]

[0064]

[0065] in, and They represent the speed and position of the ith particle at the dth iteration, m1 and m2 represent random numbers on [0,1], n1 and n2 represent individual and social learning factors, ω represents the inertia weight, and Respectively represent the optimal solutions of speed and position in the particle swarm.

[0066] Next, in order to balance the global and local aspects and improve the algorithm’s search speed and local optimization capabilities, the dynamic inertia factor can be used to improve and adjust the weight value, namely:

[0067]

[0068]

[0069]

[0070] in, and They represent the average fitness and minimum fitness of all particles at the dth iteration,

[0071] represents the fitness of the d-th generation particle, ω max and ω min Respectively represent the upper and lower limits of the weight factor.

[0072] Secondly, the measurement ratio error e λ and the rate of change of the measurement ratio error The input is fed into the improved particle swarm optimization algorithm, and the K of the air compressor fuzzy controller is output through the algorithm. Δp1 , K Δi1 , K Δd1 .

[0073] Among them, K of the air compressor fuzzy controller Δp1 , K Δi1 , K Δd1 is the output scale factor; K p0 , K i0 , K d0 is the preset value of the proportional factor, ΔK p1 , ΔK i1 , ΔK d1 is the change value of the error when the air compressor fuzzy controller outputs the fuzzy output. The final output of the control structure of the air compressor controller is the adjusted PID parameter K p1 , K i1 , K d1 :

[0074]

[0075] Again, in the same way, the cathode inlet pressure error e P and cathode inlet pressure error change rate The input is fed into the improved particle swarm optimization algorithm, and the K of the air compressor fuzzy controller is output through the algorithm. Δp2 , K Δi2 , K Δd2 .

[0076] Among them, K of the back pressure valve fuzzy controller is Δp2 , K Δi2 , K Δd2 is the output scale factor; K p0 , K i0 , K d0 is the preset value of the proportional factor, ΔK p2 , ΔK i2 , ΔK d2 is the change value of the error when the back pressure valve fuzzy controller outputs the fuzzy output. The final output of the control structure of the back pressure valve controller is the adjusted PID parameter K p2 , K i2 , K d2 :

[0077]

[0078] Among them, the controlled objects are the air compressor and the back pressure valve, and the outputs are the air compressor speed S AC And back pressure valve opening O bpv .

[0079] Finally, the control parameters are optimized by the improved particle swarm optimization algorithm. The improved PID fuzzy control algorithm is combined with the original PID control's metering ratio and back pressure. Figure 4 and Figure 5 As shown, it can be seen that the fuzzy PID control with the improved particle swarm optimization algorithm has a smaller overshoot and can achieve better control effects on the metering ratio and back pressure.

[0080] Among them, in one embodiment of the present application, the cathode metering ratio error and the cathode inlet pressure error of the fuel cell stack are determined, including: obtaining the actual metering ratio of the cathode inlet of the fuel cell stack, and determining the cathode metering ratio error according to the cathode target metering ratio and the actual cathode metering ratio of the fuel cell stack; determining the cathode inlet pressure error according to the cathode inlet target pressure and the actual cathode inlet pressure of the fuel cell stack.

[0081] For example, the embodiment of the present application can process the actual air stoichiometric ratio signal at the cathode inlet of the fuel cell stack, wherein the calculation equation of the actual signal is:

[0082]

[0083] in, is the oxygen molar flow rate at the stack inlet, I is the reaction current, n cell is the number of battery cells in the battery stack, and F is the Faraday constant, which is 96485.

[0084] Next, the stoichiometric ratio λ is calculated according to the formula set=A, minus the actual returned metering ratio signal, that is, the actual air metering ratio signal λ act , the difference between the cathode set stoichiometric ratio and the actual stoichiometric ratio can be obtained λ Secondly, the actual cathode inlet pressure P in the above step act Subtract the preset cathode inlet set pressure P set , get the difference between the actual pressure and the set pressure e P , wherein the cathode inlet set pressure can be set by a person skilled in the art to ensure stable operation of the fuel cell.

[0085] For example, Figure 6 As shown in the figure, the improved particle swarm optimization algorithm is described in detail below.

[0086] Step S601: Initialize parameters.

[0087] Step S602: Initialize particles.

[0088] Step S603: Calculate particle fitness.

[0089] Step S604: Update particle speed and position.

[0090] Step S605: Recalculate the particle fitness.

[0091] Step S606: Obtain the global optimal particle.

[0092] Step S607: Determine whether the number of iterations has been reached. If so, the optimization ends; otherwise, execute step S604.

[0093] According to the decoupling control method of the fuel cell engine air system proposed in the embodiment of the present application, the air system can be subjected to surge correction processing, and the cathode metering ratio error and cathode inlet pressure error of the fuel cell stack determined by the surge correction result of the air system are respectively input into the fuzzy PID controller based on the improved particle swarm algorithm, so as to decouple the air system of the fuel cell engine and effectively improve the stability of the operation of the air system. Thus, the problem that the decoupling of flow and pressure using the improved PR controller in the related art cannot be applied to the performance under low-frequency disturbance, resulting in the occurrence of air compressor surge in the low-power range, reducing the stability of the operation of the air subsystem, and reducing the response speed and operating efficiency of the air subsystem.

[0094] Next, the decoupling control device of the fuel cell engine air system proposed in accordance with the embodiment of the present application is described with reference to the accompanying drawings.

[0095] Figure 7It is a block diagram of a decoupling control device for a fuel cell engine air system according to an embodiment of the present application.

[0096] like Figure 7 As shown, the decoupling control device 10 of the fuel cell engine air system includes: an acquisition module 100 , a determination module 200 and a control module 300 .

[0097] Specifically, the acquisition module 100 is used to obtain the actual air compressor outlet flow, air compressor inlet pressure and air compressor outlet pressure of the air system of the fuel cell engine, and obtain the air compressor pressure ratio of the air system using the air compressor outlet pressure and air compressor inlet pressure.

[0098] The determination module 200 is used to determine the surge boundary mass flow of the air system according to the air compressor pressure ratio, and perform surge correction processing on the air system using the surge boundary mass flow and the actual flow at the air compressor outlet to obtain a surge correction result of the air system.

[0099] The control module 300 is used to determine the cathode stoichiometric ratio error and cathode inlet pressure error of the fuel cell stack based on the surge correction result, and input the cathode stoichiometric ratio error and cathode inlet pressure error into a fuzzy PID controller based on an improved particle swarm algorithm, respectively, to obtain the air compressor speed and back pressure valve opening of the air system, so as to decouple the air system of the fuel cell engine.

[0100] Optionally, in one embodiment of the present application, the determination module 200 includes: an establishing unit and a first determining unit.

[0101] Wherein, a unit is established for establishing a surge boundary equation using a plurality of target test data.

[0102] The first determination unit is used to determine the surge boundary mass flow of the air system based on the surge boundary equation and the air compressor pressure ratio.

[0103] Optionally, in one embodiment of the present application, the determination module 200 includes: a detection unit, a first acquisition unit and a processing unit.

[0104] Wherein, the detection unit is used to detect whether the surge boundary mass flow is greater than or equal to the actual flow at the air compressor outlet.

[0105] The first acquisition unit is used to acquire the bypass valve opening of the air system when it is detected that the surge boundary mass flow is greater than or equal to the actual flow at the air compressor outlet.

[0106] The processing unit is used to perform surge correction processing on the air system by utilizing the bypass valve opening.

[0107] Optionally, in one embodiment of the present application, the first acquisition unit includes: an acquisition subunit, a first determination subunit and a second determination subunit.

[0108] Among them, the acquisition subunit is used to obtain the error value between the surge boundary mass flow rate and the actual flow rate at the air compressor outlet;

[0109] The first determination subunit is used to determine a control input amount of a bypass valve of the air system according to the error value.

[0110] The second determination subunit is used to determine the opening of the bypass valve of the air system by using the control input quantity.

[0111] Optionally, in one embodiment of the present application, the control module includes: a second acquiring unit and a second determining unit.

[0112] The second acquisition unit is used to acquire the actual cathode inlet metering ratio of the fuel cell stack, and determine the cathode metering ratio error according to the cathode target metering ratio and the cathode actual metering ratio of the fuel cell stack.

[0113] The second determining unit is used to determine the cathode inlet pressure error according to the cathode inlet target pressure and the cathode inlet actual pressure of the fuel cell stack.

[0114] It should be noted that the above explanation of the embodiment of the decoupling control method of the fuel cell engine air system is also applicable to the decoupling control device of the fuel cell engine air system of this embodiment, which will not be repeated here.

[0115] According to the decoupling control device of the fuel cell engine air system proposed in the embodiment of the present application, the air system can be subjected to surge correction processing, and the cathode metering ratio error and cathode inlet pressure error of the fuel cell stack determined by the surge correction result of the air system are respectively input into the fuzzy PID controller based on the improved particle swarm algorithm, so as to decouple the air system of the fuel cell engine and effectively improve the stability of the operation of the air system. Thus, the problem that the decoupling of flow and pressure by using the improved PR controller in the related art cannot be applied to the performance under low-frequency disturbance, resulting in the occurrence of air compressor surge in the low-power range, reducing the stability of the operation of the air subsystem, and reducing the response speed and operation efficiency of the air subsystem.

[0116] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0117] A memory 801 , a processor 802 , and a computer program stored in the memory 801 and executable on the processor 802 .

[0118] When the processor 802 executes the program, the decoupling control method of the fuel cell engine air system provided in the above embodiment is implemented.

[0119] Furthermore, the electronic device further comprises:

[0120] The communication interface 803 is used for communication between the memory 801 and the processor 802 .

[0121] The memory 801 is used to store computer programs that can be executed on the processor 802 .

[0122] The memory 801 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0123] If the memory 801, the processor 802 and the communication interface 803 are implemented independently, the communication interface 803, the memory 801 and the processor 802 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0124] Optionally, in a specific implementation, if the memory 801, the processor 802 and the communication interface 803 are integrated on a chip, the memory 801, the processor 802 and the communication interface 803 can communicate with each other through an internal interface.

[0125] The processor 802 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0126] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the decoupling control method of the fuel cell engine air system is implemented as described above.

[0127] This embodiment also provides a computer program product, including a computer program, which, when executed, is used to implement the above-mentioned decoupling control method for the fuel cell engine air system.

[0128] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0129] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0130] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0131] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0132] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0133] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0134] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0135] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A decoupling control method for a fuel cell engine air system, characterized in that: The following steps are involved: Obtaining the actual air compressor outlet flow, air compressor inlet pressure and air compressor outlet pressure of the air system of the fuel cell engine, and obtaining the air compressor pressure ratio of the air system using the air compressor outlet pressure and the air compressor inlet pressure; Determining a surge boundary mass flow rate of the air system according to the air compressor pressure ratio, and performing surge correction processing on the air system using the surge boundary mass flow rate and the actual flow rate at the air compressor outlet to obtain a surge correction result of the air system; Based on the surge correction result, the cathode stoichiometric ratio error and the cathode inlet pressure error of the fuel cell stack are determined, and the cathode stoichiometric ratio error and the cathode inlet pressure error are respectively input into a fuzzy proportional integral differential PID controller based on an improved particle swarm algorithm to obtain the air compressor speed and back pressure valve opening of the air system, so as to perform decoupling control on the air system of the fuel cell engine.

2. The method according to claim 1, characterized in that Determining the surge boundary mass flow rate of the air system according to the air compressor pressure ratio includes: Establish surge boundary equation using multiple target test data; Based on the surge boundary equation and the air compressor pressure ratio, a surge boundary mass flow rate of the air system is determined.

3. The method according to claim 1, characterized in that The method of performing surge correction processing on the air system by using the surge boundary mass flow and the actual flow at the air compressor outlet includes: Detecting whether the surge boundary mass flow is greater than or equal to the actual flow at the air compressor outlet; When it is detected that the surge boundary mass flow is greater than or equal to the actual flow at the air compressor outlet, obtaining the bypass valve opening of the air system; The bypass valve opening is used to perform surge correction processing on the air system.

4. The method according to claim 3, characterized in that The obtaining of the bypass valve opening of the air system includes: Obtaining an error value between the surge boundary mass flow rate and the actual flow rate at the air compressor outlet; determining a control input amount of a bypass valve of the air system according to the error value; The control input variable is used to determine the opening of the bypass valve of the air system.

5. The method according to claim 1, characterized in that: The determining of the cathode stoichiometric ratio error and the cathode inlet pressure error of the fuel cell stack comprises: Acquiring an actual cathode inlet metering ratio of the fuel cell stack, and determining the cathode metering ratio error according to a cathode target metering ratio of the fuel cell stack and the cathode actual metering ratio; The cathode inlet pressure error is determined according to the cathode inlet target pressure of the fuel cell stack and the cathode inlet actual pressure.

6. A decoupling control device for a fuel cell engine air system, characterized in that: include: An acquisition module, used to acquire the actual flow rate at the air compressor outlet, the air compressor inlet pressure and the air compressor outlet pressure of the air system of the fuel cell engine, and to obtain the air compressor pressure ratio of the air system using the air compressor outlet pressure and the air compressor inlet pressure; a determination module, configured to determine a surge boundary mass flow rate of the air system according to the air compressor pressure ratio, and perform surge correction processing on the air system using the surge boundary mass flow rate and the actual flow rate at the air compressor outlet to obtain a surge correction result of the air system; A control module is used to determine the cathode stoichiometric ratio error and cathode inlet pressure error of the fuel cell stack based on the surge correction result, and input the cathode stoichiometric ratio error and the cathode inlet pressure error into a fuzzy proportional integral differential PID controller based on an improved particle swarm algorithm, respectively, to obtain the air compressor speed and back pressure valve opening of the air system, so as to decouple the air system of the fuel cell engine.

7. The device according to claim 6, characterized in that The determination module comprises: Establishing a unit for establishing a surge boundary equation using multiple target test data; The first determining unit is used to determine the surge boundary mass flow rate of the air system based on the surge boundary equation and the air compressor pressure ratio.

8. The device according to claim 6, characterized in that The determination module comprises: A detection unit, used to detect whether the surge boundary mass flow is greater than or equal to the actual flow at the air compressor outlet; A first acquisition unit is used to acquire the bypass valve opening of the air system when it is detected that the surge boundary mass flow is greater than or equal to the actual flow at the air compressor outlet; A processing unit is used to perform surge correction processing on the air system by using the bypass valve opening.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the decoupling control method for the fuel cell engine air system as described in any one of claims 1 to 5.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the decoupling control method of the fuel cell engine air system as described in any one of claims 1 to 5.

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